TY - JOUR
T1 - A Dynamical Systems Hypothesis of Schizophrenia
A1 - Loh, Marco
A1 - Rolls, Edmund T
A1 - Deco, Gustavo
Y1 - 2007/11/09
N2 - Author Summary One of the hallmarks of schizophrenia is the complexity and heterogeneity of the illness. We propose that part of the reason for the inconsistent symptoms may be a reduced signal-to-noise ratio and increased statistical fluctuations in different cortical brain networks. The novelty of the approach described here is that instead of basing our hypothesis purely on biological mechanisms, we develop a top-down approach based on the different types of symptoms and relate them to instabilities in attractor neural networks. Schizophrenia is characterized by cognitive, negative, and positive symptoms. We propose which characteristic effects in a dynamical system could cause these symptoms, and investigate our hypothesis in a computational model. We implement an integrate-and-fire network model and focus on the alterations of synaptic channels activated via NMDA and GABA receptors. We found that a decrease in the NMDA receptor conductance could contribute to both the cognitive and negative symptoms by reducing the neuronal firing rates and the stability of the attractor states. A reduction of both NMDA and GABA conductance causes an instability of the attractor states related to the positive symptoms. Overall, we provide a framework to discuss schizophrenia in a dynamical system framework.
JF - PLOS Computational Biology
JA - PLOS Computational Biology
VL - 3
IS - 11
UR - http://dx.doi.org/10.1371%2Fjournal.pcbi.0030228
SP - e228
EP -
PB - Public Library of Science
M3 - doi:10.1371/journal.pcbi.0030228
ER -